Yes, You Should Hire Humans
Why Investing in Human-AI Collaboration Outperforms Labor Substitution
The prevailing narrative surrounding Artificial Intelligence often frames it as a superior replacement for human labor, prioritizing efficiency and cost-saving. This perspective limits AI’s potential to achieving marginal gains through workforce reduction. However, a more potent, growth-oriented strategy exists: Hiring more entry-level workers to employ AI allows for more bandwidth and capability for growth than a firm that replaces its current entry-level operations with AI as a labor-saving tool. By positioning AI as an augmentation tool for an expanded team, a firm can achieve non-linear gains that directly justify aggressive business expansion, not retrenchment.
The central failure of a pure labor-substitution model is its focus on arithmetic cost reduction rather than geometric capacity expansion. When a firm uses AI to replace current entry-level staff, it realizes immediate, but linear, savings. In contrast, investing in an expanded workforce whose primary function is to manage, validate, and strategically apply AI output creates a significant capability multiplier. Each new hire becomes an AI-enabled operator, leveraging the technology’s speed to process information, while applying human judgment to its findings. This network of people, working together with AI, allows for multiplicities of productive capacity, transforming fixed labor costs into scalable, collaborative growth engines.
This strategic pivot is necessary because, as fast and effective as AI is, ultimately the end user of data is a person. AI can generate complex reports, synthesize vast datasets, and identify patterns at speeds impossible for humans, but these outputs only gain value when a person interprets them, applies contextual intelligence, and translates them into organizational decisions or client solutions. The marginal cost of AI processing is low, but the marginal value of human oversight in validating its conclusions and addressing corner cases is immense. By expanding the entry-level workforce, the firm increases its human touchpoints for data application, ensuring that AI’s speed is paired with judgment and accountability across all operational domains.
The optimal human-AI pairing can achieve a significant productivity uplift, with a large study in knowledge work suggesting increases up to 43% for consultants who ranked in the bottom half of performance, effectively acting as a leveler across performance distribution (Frank et al., 2023). Furthermore, this augmentation strategy generates non-linear returns, with organizations leveraging generative AI augmentation achieving 2.5x higher revenue growth compared to competitors focusing only on pure automation (Accenture, 2024). This exponential return, which is reinvested back into organizational bandwidth, directly supports and justifies the upfront cost of aggressive expansion, making it a sustainable and superior strategic choice over simple headcount reduction.
Furthermore, this collaborative approach delivers a critical strategic advantage in human capital management. The interaction between new workers and advanced AI systems inherently aids the onboarding process, shifting entry-level training from repetitive task execution to high-value skill development, such as prompt engineering and data validation. This transition, which moves staff toward complex, augmentable tasks (WEF, 2023), is supported by empirical data: low-skilled agents in customer service saw a 35% productivity boost when assisted by AI, while high-skilled counterparts saw close to zero gain (Mollick et al., 2023). By eliminating entry-level roles, a firm sacrifices these disproportionate gains for simple labor saving, while still incurring the maintenance cost of the AI platform.
Crucially, the data supports this focus: “Less skilled and less experienced workers improve significantly across all productivity measures, including a 30% increase in the number of issues resolved per hour.” This immediate boost in effectiveness and sense of competence makes the job significantly more engaging, and research indicates that AI-enabled personalization of work and reduction in tedious tasks leads to improved job satisfaction and retention rates (Deloitte; Horton International, 2024). Without as many tedious tasks required, this opens up more time for employee development and bakes redundancy into the organization. The strategy thus simultaneously reduces labor market risk while building a future-proof, highly skilled workforce ready to execute aggressive growth mandates.
In conclusion, this approach repositions AI from an accounting item dedicated to cost containment to a core strategic asset dedicated to capacity expansion. By funding an aggressive expansion of the entry-level workforce to effectively utilize AI, a firm maximizes both its technological investment and its human capital. This model generates a level of bandwidth and operational capability that fundamentally justifies not merely maintaining but aggressively expanding the firm’s ambition and market reach.
References
Accenture (2024). Augmentation vs. Automation: How AI Transforms Workforce Efficiency. Aura Intelligence Blog. Retrieved from https://blog.getaura.ai/ai-augmentation-automation
Deloitte (2024). AI is likely to impact careers. How can organizations help build a resilient early career workforce?. Deloitte Insights. Retrieved from https://www.deloitte.com/us/en/insights/topics/talent/ai-in-the-workplace.html
Frank, H. D., Mollick, E., et al. (2023). BCG AI in the workplace study shows junior employees benefit more than their seniors. Fanatical Futurist Blog. (Referencing the Boston Consulting Group/Academic study). Retrieved from https://www.fanaticalfuturist.com/2023/09/bcg-ai-in-the-workplace-study-shows-junior-employees-benefit-more-than-their-seniors/
Horton International (2024). How AI is Transforming Employee Retention Strategies. Horton International Blog. Retrieved from https://hortoninternational.com/how-ai-is-transforming-employee-retention-strategies/
Mollick, E., et al. (2023). (Referencing the Fortune 500 Customer Service study). BCG AI in the workplace study shows junior employees benefit more than their seniors. Fanatical Futurist Blog. Retrieved from https://www.fanaticalfuturist.com/2023/09/bcg-ai-in-the-workplace-study-shows-junior-employees-benefit-more-than-their-seniors/
World Economic Forum (WEF) (2023). Jobs of Tomorrow: Will AI automate or augment future work?. World Economic Forum Agenda. Retrieved from https://www.weforum.org/stories/2023/09/ai-automation-augmentation-workplace-jobs-of-tomorrow/